Multiple Access (MA) schemes are used to make a shared communications channel simultaneously available to several users or applications that wish to transmit their data streams. Next generation wireless systems will have to face the demand for higher aggregate data rates while being capable of providing reliable communication to many more simultaneous users and applications than current systems. Such high capacity will be achieved by an increasingly efficient use of the channel's physical resources.
Overloading is a paradigm according to which, in a transmission system, several data streams are multiplexed onto the same time-frequency-space Resource Elements (REs), thus resulting in increased data rates and spectral efficiencies. Applying the overloading concept to the MA context, OverLoaded Multiple Access (OLMA) schemes have been conceived which are able to provide significantly higher Spectral Efficiency (SE) than conventional MA schemes.
OLMA schemes can be classified based on the Domain of Separation (DoS) of users/streams:
Power DoS: e.g. Non Orthogonal Multiple Access (NOMA) schemes. Here, a far user and a near user are multiplexed on the same time-frequency-space REs. The scheme is based on the transmission of superposed signals with different amplitudes.
Constellation DoS: e.g., Constellation Expansion Multiple Access (CEMA). Here, subsets of constellation symbols are allocated to different users/streams.
Spreading Sequences DoS: e.g., Low Density Spread (LDS), Code Division Multiple Access (CDMA), and LDS Orthogonal Frequency Division Multiplexing (OFDM). These schemes are based on the allocation of different sparse sequences to different users/streams.
Spread Superposition Codebooks DoS: e.g., LDS-CDMA, LDS-OFDM, Sparse Code Multiple Access (SCMA), Interleave-Division Multiple Access (IDMA). These schemes are based on user-specific spreading and modulation codebooks that aim to maximize the minimum Euclidean distance between the sparse spread signals of different users/streams.
Non-Spread Superposition Codebooks DoS: e.g., Trellis-Coded Multiple Access (TCMA) and Enhanced Trellis-Coded Multiple Access (ETCMA). These schemes are based on TCM with stream-specific interleaving, resulting in stream-specific non-spread codebooks.
Practical NOMA methods can be designed starting from different scenarios, where each scenario is characterized by a specific optimization criterion or target for the selection of transmission parameters, leading to quite different solutions. However, all NOMA transmission methods have to ensure reliable separation/detection, demodulation and decoding of each individual multiplexed stream at the intended UEs.
In the first overloading scenario, the optimization target is the maximization of the aggregate Downlink (DL) spectral efficiency (of one cell) by simultaneous transmission to the UEs experiencing similar physical communication channel qualities. The User Equipments (UEs) that report to the transmitter similar Channel Quality Indicators (CQI) are grouped by the scheduler into the same category, and then served by the same transmission resources when the instantaneous channel conditions are the best at these resources. The corresponding NOMA methods thus preserve the same data rate, the same transmitted energy per bit of each multiplexed stream, and the same scheduler design as if each of the multiplexed streams would have been transmitted alone on observed time-frequency-space resources. It further means that the transmitted power per RE is increased proportionally to the overloading factor, i.e. the number of multiplexed streams. The NOMA schemes designed using this principle include, for example, Low-Density Spread (LDS) Multiple Access (LDSMA), Trellis-Coded Multiple Access (TCMA) and its enhanced version (ETCMA), Constellation-Expansion Multiple Access (CEMA), etc.
In the second overloading scenario, the target is to increase the number of UEs served per RE, but without increasing the transmitted power per RE. The direct consequence of conserving the transmitted power per RE is that the achievable data rates of each of multiplexed UE signals are lower than if each of them would have been transmitted separately. An additional target is to do multiplexing in such a way that the aggregate rate of concurrently served UEs is larger than the aggregate rate that can be obtained by time division multiplexing of these UEs (where each transmission interval is split into subintervals corresponding to different UEs). It can be shown that this target can be achieved only if the received Signal-to-Noise Ratios (SNRs) of the multiplexed UEs are not equal. Indeed, the higher the SNR difference, the higher is the gain one can expect from concurrent transmission. It should be noted that this target is not equivalent to maximizing the aggregate data rate per RE, as it can be shown that the aggregate data rate cannot be larger than the maximum single UE data rate that can be obtained for the UE with the highest received SNR. The practical implementation of such NOMA scheme is based on the weighted amplitude superposition of error-correction code words for (typically two) different UEs, where UE-specific amplitude scaling keeps the total power per RE equal to the RE power for single UE transmission. We shall refer to such scheme as amplitude-weighted NOMA (AW-NOMA). Each amplitude scaling coefficient uniquely determines the maximum code rate for the corresponding UE.
The increased SE of any OLMA scheme is achieved at the expense of increased transmitted power for each multiplexed stream/user. This increase can be characterized by the so-called single-stream SNR loss, a feature that is defined as a function of the aggregate spectral efficiency defined asSE(K,SNR)=(1−BLER(SNR))Rm0K [bits/s/Hz].  (1)
Here, BLER indicates the block error rate, R is the channel code rate, m0 is the modulation order in bits per symbol and K is the overloading factor, i.e. the number of multiplexed streams. The SE is a function of the SNRSE∞(K)=limSNR→∞SE(K,SNR)  (2)
and eq. (2) indicates the asymptotic Aggregate Spectral Efficiency (ASE). The relevant metric for the evaluation of transmission schemes is the single-stream SNR loss ΔSNR(K,ρ), which is defined as the increase of SNR with respect to the single-stream SNR required by the receiver to achieve a given ratio ρ of the ASE when the overloading factor is K>1, i.e.,ΔSNR(K,ρ)=SNR(SE(K,SNR)=ρSE∞(K))−SNR(SE(1,SNR)=ρSE∞(1)).  (3)